It is often necessary or desirable to detect a signal in a compound signal. For example, most motorists have detected an annoying sound in the cabin of their car while driving the car around. In order to identify the annoying sound (i.e. the signal) from background noise caused by the car engine and road noise, etc (i.e. the compound signal) one of a number of different techniques are used. In one technique, a trained technician may, sit in the car whilst it is motion and use his trained ear to identify the annoying sound and its cause. The cause of the annoying sound may be, for example, due to a clutch clicking or a seat squeaking. A technician can identify the source of the annoying sound and then rectify it. In another example, the sound in the cabin of the car may be recorded and processed mathematically. Changes in the recorded signal may be attributed to the annoying sound, and these changes can be detected using the mathematical processing. One way of processing the signal is to discretise it into a number of points (or, conversely, recording the signal in a discretised manner, for example by sampling the signal). The discretised recorded signal can be split into a number of segments. These segments can be characterised by determining, in each segment, the standard deviation of the segments divided by the mean value of recorded data within the segment (which is sometimes referred to as the determining the variation coefficient for the segment).